Emerging whole-cell modeling principles and methods
Abstract
Whole-cell computational models aim to predict cellular phenotypes from genotype by representing the entire genome, the structure and concentration of each molecular species, each molecular interaction, and the extracellular environment. Whole-cell models have great potential to transform bioscience, bioengineering, and medicine. However, numerous challenges remain to achieve whole-cell models. Nevertheless, researchers are beginning to leverage recent progress in measurement technology, bioinformatics, data sharing, rule-based modeling, and multi-algorithmic simulation to build the first whole-cell models. We anticipate that ongoing efforts to develop scalable whole-cell modeling tools will enable dramatically more comprehensive and more accurate models, including models of human cells.
Cite
@article{arxiv.1710.02431,
title = {Emerging whole-cell modeling principles and methods},
author = {Arthur P. Goldberg and Balázs Szigeti and Yin Hoon Chew and John A. P. Sekar and Yosef D. Roth and Jonathan R. Karr},
journal= {arXiv preprint arXiv:1710.02431},
year = {2019}
}
Comments
10 pages, 2 figures, 7 supplementary tables